Special Issue Information

Dear Colleagues,

The consensus among a majority of climate scientists is that we should expect an increase in the number and severity of weather events in coming years. This Special Issue will comprise a selection of papers assessing the impacts of and vulnerability to weather-related natural disasters. Research papers addressing the ways in which disasters affect and are affected by poverty and income disparity, social capital, and emerging technologies are welcome. Covered topics include: (1) the ways in which disasters may lead to violence and/or cooperation; (2) how disasters may affect poverty, income disparity, social capital, and technology adoption; and (3) how poverty, income disparity, social capital, and emerging technologies play a role in determining disaster vulnerability. Papers selected for this Special Issue are subject to a rigorous peer-review procedure with the aim of rapid and wide dissemination of research results, developments, and applications.

Prof. Mark SkidmoreProf. Hideki ToyaGuest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

We present an empirical study to systemically estimate flooding impacts, linking across scales from individual firms through to the macro levels in China. To this end, we combine a detailed firm-level econometric analysis of 399,356 firms with a macroeconomic input-output model to estimate
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We present an empirical study to systemically estimate flooding impacts, linking across scales from individual firms through to the macro levels in China. To this end, we combine a detailed firm-level econometric analysis of 399,356 firms with a macroeconomic input-output model to estimate flood impacts on China’s manufacturing sector over the period 2003–2010. We find that large flooding events on average reduce firm outputs (measured by labor productivity) by about 28.3% per year. Using an input-output analysis, we estimate the potential macroeconomic impact to be a 12.3% annual loss in total output, which amounts to 15,416 RMB billion. Impacts can propagate from manufacturing firms, which are the focus of our empirical analysis, through to other economic sectors that may not actually be located in floodplains but can still be affected by economic disruptions. Lagged flood effects over the following two years are estimated to be a further 5.4% at the firm level and their associated potential effects are at a 2.3% loss in total output or 2,486 RMB billion at the macro-level. These results indicate that the scale of economic impacts from flooding is much larger than microanalyses of direct damage indicate, thus justifying greater action, at a policy level and by individual firms, to manage flood risk.
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Understanding storm surge inundation risk is essential for developing countermeasures and adaptation strategies for tackling climate change. Consistent assessment of storm surge inundation risk that links probability of hazard occurrence to distribution of economic consequence are scarce due to the lack of historical
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Understanding storm surge inundation risk is essential for developing countermeasures and adaptation strategies for tackling climate change. Consistent assessment of storm surge inundation risk that links probability of hazard occurrence to distribution of economic consequence are scarce due to the lack of historical data and uncertainty of climate change, especially at local scales. This paper proposes a simulation-based method to construct exceedance probability (EP) curves for representing storm surge risk and identifying the economic impact of climate change in the coastal areas of Ise Bay, Japan. The region-specific exceedance probability curves show that risk could be different among different districts. The industry-specific exceedance probability curves show that manufacturing, transport and postal activities, electricity, gas, heat supply and water, and wholesale and retail trade are the most affected sectors in terms of property damage. Services also need to be of concern in terms of business interruption loss. Exceedance probability curves provide complete risk information and our simulation-based approach can contribute to a better understanding of storm surge risk, improve the quantitative assessment of the climate change-driven impacts on coastal areas, and identify vulnerable regions and industrial sectors in detail.
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Social capital plays a significant role in post-disaster community participation and disaster recovery. This study divides social capital into three aspects: Cognition, structure, and relation, and discusses the impact of these factors on community participation in post-disaster recovery. Through data analysis, we found
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Social capital plays a significant role in post-disaster community participation and disaster recovery. This study divides social capital into three aspects: Cognition, structure, and relation, and discusses the impact of these factors on community participation in post-disaster recovery. Through data analysis, we found that a self-organized relationship villager network had a positive effect on villagers’ participation in voluntary community activities after an earthquake, while the local cadre relationship network had a negative impact. However, the latter could encourage villagers to participate in disaster-recovery activities organized by the local government. These findings indicate that the mobilization mechanism for post-disaster local-government reconstruction and community self-organization are the same, both coming through the social-acquaintance network, a type of noninstitutionalized social capital. The implication of this study suggests that local government should attach much importance to the construction and integration of social networks in earthquake-stricken areas to cultivate community social capital.
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Damage caused by natural disasters produces the difference of damage size not only according to damage volume or size, but a national economic level. In addition, budgets and aids should be constantly acquired for disaster management since natural disasters sporadically or irregularly occur.
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Damage caused by natural disasters produces the difference of damage size not only according to damage volume or size, but a national economic level. In addition, budgets and aids should be constantly acquired for disaster management since natural disasters sporadically or irregularly occur. This study proposed disaster management methods by countries considering natural disaster damage documents and economic indicators from 1900 to 2017 among 187 countries in the world. It developed a damage prediction formula considering damage documents of previous natural disasters, economic indicators by countries, and basic indicators as disaster management methods by countries. Independent variables of the damage prediction formula include GDP, population, and area. It applied multiple regression analysis and calculated average human losses due to death, human losses affected, and damage costs by countries. Regarding the adjusted R² of the natural disaster damage prediction formula, the human losses from deaths mean was 0.893, the human losses affected mean was 0.915, and the damage costs mean was 0.946, which had higher explanatory powers. Therefore, results from this study are considered to calculate quantitative damage sizes considering uncertain damage sizes of natural disasters, economic indicators by countries, and are used as indicators for disaster management.
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Aid from the government can play a critical role as a risk-coping device in a post-disaster situation if the recipients are properly targeted. We analyze the accuracy of disaster aid targeting and self-reporting bias in disaster damage and aid receipt by combining (i)
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Aid from the government can play a critical role as a risk-coping device in a post-disaster situation if the recipients are properly targeted. We analyze the accuracy of disaster aid targeting and self-reporting bias in disaster damage and aid receipt by combining (i) satellite images (objective information on flood damage), (ii) administrative records (objective information on post-flood aid receipt), and (iii) unique survey data (self-reported information on damage assessment and aid receipt) on a large-scale flooding in 2012 in the Philippines. We find that damage is over-reported while aid receipt is under-reported, and as a result, the estimated targeting accuracy based on self-reported information is substantially downward-biased.
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Hurricanes and extreme weather events can cause widespread damage and disruption to infrastructure services and consequently delay household and community recovery. A subset of data from a cross-sectional survey of 989 households in central and south Florida is used to examine the effects
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Hurricanes and extreme weather events can cause widespread damage and disruption to infrastructure services and consequently delay household and community recovery. A subset of data from a cross-sectional survey of 989 households in central and south Florida is used to examine the effects of Hurricane Irma on post-disaster recovery eight months after the landfall. Using logistic regression modeling, we find that physical damage to property, disruption of infrastructure services such as loss of electric power and cell phone/internet services and other factors (i.e., homeowner’s or renter’s insurance coverage, receiving disaster assistance and loss of income) are significant predictors of post-disaster recovery when controlling for age and race/ethnicity.
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In this study, we conduct an estimation study of the damage costs, recovery costs, and human losses in the case of natural disasters in the Republic of Korea. This research method analyzed human losses, damage costs, and recovery costs caused by natural disasters
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In this study, we conduct an estimation study of the damage costs, recovery costs, and human losses in the case of natural disasters in the Republic of Korea. This research method analyzed human losses, damage costs, and recovery costs caused by natural disasters that swept across the Republic of Korea over the past 16 years, from 2000 to 2015, including extreme wind, heavy snowfall, typhoon, wind wave, and heavy rainfall. Damage status and trend of occurrence were reviewed for each year’s human losses, damage costs, and recovery costs. We propose a calculating equation of the linear regression equation that estimates damage costs and recovery costs considering human losses. The correlation coefficient was 0.898 for the estimation of human losses and damage costs, and 0.889 for the estimation of human losses and recovery costs. In addition, the correlation of both equations was found to be 166% of damage costs when calculating recovery costs. The results of this study can be used as descriptive statistical data to estimate damage costs and recovery costs according to human losses in case of natural disasters.
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In this paper, we examine whether disasters affect social trust levels using South Korean panel data from 2014–2016. We also investigate whether the effects of disasters on social trust differ depending on the type of disaster. We consider four types of disasters: typhoons,
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In this paper, we examine whether disasters affect social trust levels using South Korean panel data from 2014–2016. We also investigate whether the effects of disasters on social trust differ depending on the type of disaster. We consider four types of disasters: typhoons, heavy rain, heavy snow and strong winds and waves. Our findings show that although all of these disasters influence the level of generalized social trust, each type has separate impacts. In our findings, there is a statistically significant positive relationship between cumulative damage costs per capita and social trust levels for heavy rain, heavy snow and strong winds and waves but we find the opposite result for typhoons. In the disaster recovery process, it is possible for social trust to be strengthened and weakened at the same time. Social trust can develop when victims such as neighbors and firefighters interact with others. Conversely, when a local government responds slowly to a disaster, dissatisfaction and discontent toward it can increase and this could weaken social trust. Moreover, disaster-affected individuals may be more competitive over limited resources, resulting in conflicts among them. Thus, we argue that the net effects of disasters on social trust levels can differ based on the speed of government responses to disasters and on active support for the victims from people such as neighbors.
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A global revolution in information and communication technologies (ICT) has occurred over the past few decades, emerging first in industrialized countries and then in developing countries. While researchers have examined many facets of the ICT revolution, relatively little work has systematically examined the
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A global revolution in information and communication technologies (ICT) has occurred over the past few decades, emerging first in industrialized countries and then in developing countries. While researchers have examined many facets of the ICT revolution, relatively little work has systematically examined the degree to which ICT has reduced natural disaster vulnerability. In this article we use cross-country data over the 1980–2013 period to estimate the relationship between newly-emerging cell phone access/use and disaster-induced fatalities. Our estimates suggest that a one-standard-deviation increase in cell phone usage reduces disaster fatalities by nearly one half. The estimated effect increases to almost three quarters for geologic events where people are typically afflicted without warning. The largest marginal benefit from cell phones in terms of saving lives come from events where there is typically no warning, thus, many are caught by surprise; cell phones are used to call for help and coordinate assistance.
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The US government provided $2.6 billion of small business administration (SBA) disaster loans to individuals and businesses in Mississippi after Hurricane Katrina in 2005. However, existing literature has not fully explored the firm-level effects of post-disaster loan aid, specifically, the effect on small
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The US government provided $2.6 billion of small business administration (SBA) disaster loans to individuals and businesses in Mississippi after Hurricane Katrina in 2005. However, existing literature has not fully explored the firm-level effects of post-disaster loan aid, specifically, the effect on small businesses. The objective of this article is to examine whether SBA disaster loans played a significant role in the performance of small businesses after Hurricane Katrina. Data from a sample of 287 small businesses in Mississippi that were operating before Hurricane Katrina and still operating in 2013 were used in the analysis. Two hypotheses were tested: (1) small business owners that received SBA disaster loans have higher revenue change compared to before Katrina than those who did not receive the loan; (2) small business owners that received SBA disaster loans perceived their businesses to have higher revenue than before Katrina. Receiving a SBA disaster loan played a positive and statistically significant role in determining the actual revenue change and owners’ perception of revenue.
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With the shift from a hazard-centered disaster paradigm to one that places emphasis on vulnerability and resilience, disasters triggered by natural hazards have begun to be perceived as unnatural occurrences. To date, the theoretical conceptualization and empirical measures of vulnerability and resilience remain
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With the shift from a hazard-centered disaster paradigm to one that places emphasis on vulnerability and resilience, disasters triggered by natural hazards have begun to be perceived as unnatural occurrences. To date, the theoretical conceptualization and empirical measures of vulnerability and resilience remain subjects of contentions. This survey of the empirical economic literature aims to describe the progress made in the conceptualization and measurement of the economic dimensions of vulnerability and resilience in the context of natural hazards, and to provide useful insights for policy-making. Economic vulnerability and economic resilience, interacting with the hazard itself, and the exposure of populations and physical assets, are considered to be critical determinants of the resulting impacts of disasters. The empirical evidence provides systematic support for the hypothesis that apart from the characteristics of the hazards, the potential for people and economies to avoid adverse impacts and their capacity to withstand and rebound from a disaster are influenced by a confluence of socio-economic factors.
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